The research and development of teleradiology and telemedicine systems has progressed through many technical and clinical endeavors. When dealing with large volume image transmission and storage, lossy data compression is an outstanding issue in medical applications to which current techniques were not designed to address. The technical objectives of this SBIR project are to develop a lossless as well as an error-controllable compression scheme for medical image compression. Based on our recent research, we found that any wavelet transform can be implemented in an integer form prior to the coding. We would like to study the technical advantages by using the integer wavelet decomposition method and to develop software as compression tools for clinical images such as chest radiographs, CT, and MR images. We will compare the compression results (i.e., compression ratio and computation speed) of the proposed compression method with those of the current wavelet compression method (e.g., embedded zero-tree for wavelet compression). In Phase II, the research and development will be extended to 3-D slab wavelet transform and adaptive wavelet compression for the optimization of this SBIR study. Other related software functions and the user interface will be included to facilitate the use of the system. As the field of telemedicine is rapidly growing, we believe that the development of dedicated compression module for economical storage and fast communication of patient data (particularly for patient images) is necessary. This SBIR is designed to address the related technical issues with a strong clinical consideration. PROPOSED COMMERCIAL APPLICATIONS: This development will be inseparable form the field of telemedicine as a whole in the future. The commercial potential of the proposed product is very high.